Optimization¶
Solves the optimization problem of continuous/discrete variables, given a model function \(f(x)\) given the form:
Where:
\(f: \mathbb{R}^n \rightarrow \mathbb{R}\): is the objective function to be maximized over the \(n\)-variable vector \(x\)
\(g_i(x) \leq 0\): are a set of inequality contraints to be satisfied.
Usage¶
e["Problem"]["Type"] = "Optimization"
Variable-Specific Settings¶
These are settings required by this module that are added to each of the experiment’s variables when this module is selected.
- Granularity
Usage: e[“Variables”][index][“Granularity”] = real number
Description: Specifies the granularity of a discrete variable, a granularity of 1.0 means that the variable can only take values in (.., -1.0, 0.0, +1.0, +2.0, ..) where the levels are set symmetric around the initial mean (here 0.0).
- Name
Usage: e[“Variables”][index][“Name”] = string
Description: Defines the name of the variable.
Configuration¶
These are settings required by this module.
- Num Objectives
Usage: e[“Problem”][“Num Objectives”] = unsigned integer
Description: Number of return values to expect from objective function.
- Objective Function
Usage: e[“Problem”][“Objective Function”] = Computational Model
Description: Stores the function to evaluate.
- Constraints
Usage: e[“Problem”][“Constraints”] = List of Computational Model
Description: Stores constraints to the objective function.
Default Configuration¶
These following configuration will be assigned by default. Any settings defined by the user will override the given settings specified in these defaults.
{ "Constraints": [], "Has Discrete Variables": false, "Num Objectives": 1 }
Variable Defaults¶
These following configuration will be assigned to each of the experiment variables by default. Any settings defined by the user will override the given settings specified in these defaults.
{ "Granularity": 0.0 }